Weighted Combination of Analyte Values for Multiple Sensing Areas

The present application claims the benefit of priority to U.S. Provisional Application No. 63/704,298, filed Oct. 7, 2024, which is incorporated herein by reference in its entirety.

This disclosure relates to weighted combination of analyte values for multiple sensing areas (SAs).

Analyte monitoring systems have been configured to generate analyte values using an implantable analyte sensor within a living body and determine a level (e.g., an amount and/or concentration) of an analyte (e.g., glucose) in the living body (e.g., in interstitial fluid or blood of the living body) based on the generated analyte values. However, certain challenges presently exist with respect to analyte monitoring. For example, in analyte monitoring systems having an analyte sensor including only a single sensing area (SA), the accuracy of the determined analyte level depends greatly on the performance of the single SA, which varies based on factors such as an extent to which analyte indicator molecules used by the sensing area have degraded, among other potential error causing issues. For another example, in analyte monitoring systems having an analyte sensor including multiple sensing areas, the analyte monitoring system may be configured to generate analyte values for each of the different SAs independently, and the amount and/or concentration of the analyte (a.k.a., “overall analyte level”) may be determined based on a combination of the analyte values for the different SAs. However, erroneous analyte values from one SA will reduce the accuracy of the determined overall analyte level. Thus, there is a need for improved analyte monitoring systems.

Aspects may relate to an analyte monitoring system having an analyte sensor including multiple sensing areas (SAs), and the analyte monitoring system may be configured to generate analyte values for each of the different SAs independently and to determine the amount and/or concentration of the analyte (a.k.a., “overall analyte level”) based on a combination of the analyte values for the different SAs. In scenarios where analyte values determined for one SA of the analyte sensor are substantially different from analyte values determined for other SAs of the analyte sensor, the diverged analyte values may be due to an error. The analyte monitoring system, in calculating the overall analyte level, may treat the diverged analyte values differently than the non-diverged analyte values. More specifically, the analyte monitoring system may de-weight the diverged analyte values (e.g., low quality measurements) in calculating the overall analyte level.

508 In one aspect, a method may be performed by an analyte monitoring system comprising an analyte sensor. The method may include generating a first set of one or more analyte values using first measurement electronics of a first sensing area (SA) of the analyte sensor. The method may include generating a second set of one or more analyte values using second measurement electronics of a second SA of the analyte sensor. The first and second SAs may be different. The method may include generating a third set of one or more analyte values using third measurement electronics of a third SA of the analyte sensor. The first, second, and third SAs may be different. The method may include determining (s) a distribution value based on a plurality of sets of analyte values including the first, second, and/or third sets of analyte values. The distribution value may indicate a distribution of the plurality of sets of analyte values. The method may include determining a combined analyte level based at least on the plurality of sets of analyte values and the distribution value.

In some aspects, the first set of analyte values may include a plurality of analyte values generated for different instances of time using the first measurement electronics of the first SA of the analyte sensor, the second set of analyte values may include a plurality of analyte values generated for the different instances of time using the second measurement electronics of the second SA of the analyte sensor, and the third set of analyte values may include a plurality of analyte values generated for the different instances of time using the third measurement electronics of the third SA of the analyte sensor.

In some aspects, the method may include: determining whether the first set of analyte values satisfies a condition; determining whether the second set of analyte values satisfies the condition; determining whether the third set of analyte values satisfies the condition; and, based on determining that the first and second sets of analyte values do not satisfy the condition and the third set of analyte values satisfies the condition, not selecting the first and second SAs and selecting the third SA, wherein the combined analyte level is determined based on the selection of the third SA. In some aspects, the analyte sensor may include a plurality of SAs including the first, second, and third SAs, and the method may include generating the plurality of set of analyte values using measurement electronics of the plurality of SAs of the analyte sensor. In some aspects, determining the distribution value may include: calculating a first tendency value representing the third set of analyte values and calculating a second tendency value representing the plurality of sets of analyte values. In some aspects, whether the third set of analyte values satisfies the condition may be determined based at least on the first tendency value, the second tendency value, and the distribution value. In some aspects, the first tendency value may be one of a mean or a median of the third set of analyte values, the second tendency value may be one of a mean or a median of the plurality of sets of analyte values, and the distribution value may be one of a standard deviation, an interquartile range, or an interdecile range of the plurality of sets of analyte values.

In some aspects, determining whether the third set of analyte values satisfies the condition may include: calculating a comparative value based on the first tendency value, the second tendency value, and the distribution value; determining whether the comparative value is greater than a threshold value; and determining that the third set of analyte values satisfies the condition based on whether the comparative value is greater than the threshold value. In some aspects, the comparative value may be calculated as follows:

1 2 3 1 2 2 where d is the comparative value, Cis a first constant, Cis a second constant, Cis a third constant, Tis the first tendency value, Tis the second tendency value, and Dis the distribution value.

In some aspects, if the third set of analyte values is determined to satisfy the condition, the distribution value may be determined not based on the third set of analyte values.

In some aspects, determining the combined analyte level may include: calculating a first SA analyte level for the first SA based on the first set of analyte values; determining a first weight for the first SA analyte level; calculating a second SA analyte level for the second SA based on the second set of analyte values; determining a second weight for the second SA analyte level; calculating a third SA analyte level for the third SA based on the third set of analyte values; and determining a third weight for the third SA analyte level. In some aspects, the combined analyte level may be determined based on the first SA analyte level, the first weight, the second SA analyte level, the second weight, the third SA analyte level, and the third weight. In some aspects, the first weight may be determined based at least on: the first SA analyte level, a tendency value representing the plurality of sets of analyte values, and the distribution value; the second weight may be determined based at least on: the second SA analyte level, the tendency value, and the distribution value; and the third weight may be determined based at least on: the third SA analyte level, the tendency value, and the distribution value.

In some aspects, the first weight may have a negative correlation with a difference between the first SA analyte level and the tendency value increases, the second weight may have a negative correlation with a difference between the second SA analyte level and the tendency value increases, and the third weight may have a negative correlation with a difference between the third SA analyte level and the tendency value increases. In some aspects, the tendency value may be one of a mean or a median of the plurality of sets of analyte values, and the distribution value may be one of a standard deviation, an interquartile range, or an interdecile range of the plurality of sets of analyte values. In some aspects, the first weight may be equal to

the second weight may be equal to

and the third weight may be equal to

1 SA1 SA2 SA3 2 3 where Cis a constant, ALis the first SA analyte level, ALis the second SA analyte level, ALis the third SA analyte level, Cis a constant, CT is the tendency value, Cis a constant determining how quickly the first, second, and third weights change depending on a difference between an SA analyte level and the tendency value, and S is the distribution value.

In another aspect, an analyte monitoring system may be provided including an analyte sensor and a user device. The analyte monitoring system may be configured to generate a first set of one or more analyte values using first measurement electronics of a first sensing area (SA) of the analyte sensor and generate a second set of one or more analyte values using second measurement electronics of a second SA of the analyte sensor. The first and second SAs may be different. The analyte monitoring system may be configured to generate a third set of one or more analyte values using third measurement electronics of a third SA of the analyte sensor, and the first, second, and third SAs may be different. The analyte monitoring system may be configured to determine a distribution value based on a plurality of sets of analyte values including the first, second, and/or third sets of analyte values, and the distribution value may indicate a distribution of the plurality of sets of analyte values. The analyte monitoring system may be configured to determine a combined analyte level based at least on the plurality of sets of analyte values and the distribution value.

In some aspects, the first set of analyte values may include includes a plurality of analyte values generated for different instances of time using the first measurement electronics of the first SA of the analyte sensor, the second set of analyte values may include a plurality of analyte values generated for the different instances of time using the second measurement electronics of the second SA of the analyte sensor, and the third set of analyte values may include a plurality of analyte values generated for the different instances of time using the third measurement electronics of the third SA of the analyte sensor.

In some aspects, the analyte monitoring system may be configured to: determine whether the first set of analyte values satisfies a condition; determine whether the second set of analyte values satisfies the condition; determine whether the third set of analyte values satisfies the condition; and, based on determining that the first and second sets of analyte values do not satisfy the condition and the third set of analyte values satisfies the condition, not select the first and second SAs and selecting the third SA. In some aspects, the combined analyte level may be determined based on the selection of the third SA. In some aspects, the analyte sensor may include a plurality of SAs including the first, second, and third SAs, and the analyte monitoring system may be configured to generate the plurality of set of analyte values using measurement electronics of the plurality of SAs of the analyte sensor. In some aspects, determining the distribution value may include: calculating a first tendency value representing the third set of analyte values and calculating a second tendency value representing the plurality of sets of analyte values. In some aspects, whether the third set of analyte values satisfies the condition may be determined based at least on the first tendency value, the second tendency value, and the distribution value. In some aspects, the first tendency value may be one of a mean or a median of the third set of analyte values; the second tendency value may be one of a mean or a median of the plurality of sets of analyte values; and the distribution value may be one of a standard deviation, an interquartile range, or an interdecile range of the plurality of sets of analyte values.

In some aspects, determining whether the third set of analyte values satisfies the condition may include: calculating a comparative value based on the first tendency value, the second tendency value, and the distribution value; determining whether the comparative value is greater than a threshold value; and determining that the third set of analyte values satisfies the condition based on whether the comparative value is greater than the threshold value. In some aspects, the comparative value may be calculated as follows:

1 2 3 1 2 2 where d is the comparative value, Cis a first constant, Cis a second constant, Cis a third constant, Tis the first tendency value, Tis the second tendency value, and Dis the distribution value.

In some aspects, if the third set of analyte values is determined to satisfy the condition, the distribution value may be determined not based on the third set of analyte values.

In some aspects, determining the combined analyte level may include: calculating a first SA analyte level for the first SA based on the first set of analyte values; determining a first weight for the first SA analyte level; calculating a second SA analyte level for the second SA based on the second set of analyte values; determining a second weight for the second SA analyte level; calculating a third SA analyte level for the third SA based on the third set of analyte values; and determining a third weight for the third SA analyte level. In some aspects, the combined analyte level may be determined based on the first SA analyte level, the first weight, the second SA analyte level, the second weight, the third SA analyte level, and the third weight. In some aspects, the first weight may be determined based at least on: the first SA analyte level, a tendency value representing the plurality of sets of analyte values, and the distribution value; the second weight may be determined based at least on: the second SA analyte level, the tendency value, and the distribution value; and the third weight may be determined based at least on: the third SA analyte level, the tendency value, and the distribution value. In some aspects, the first weight may have a negative correlation with a difference between the first SA analyte level and the tendency value increases; the second weight may have a negative correlation with a difference between the second SA analyte level and the tendency value increases; and the third weight may have a negative correlation with a difference between the third SA analyte level and the tendency value increases.

In some aspects, the tendency value may be one of a mean or a median of the plurality of sets of analyte values, and the distribution value may be one of a standard deviation, an interquartile range, or an interdecile range of the plurality of sets of analyte values. In some aspects, the first weight may be equal to

the second weight may be equal to

and the third weight may be equal to

1 SA1 SA2 SA3 2 3 where Cis a constant, ALis the first SA analyte level, ALis the second SA analyte level, ALis the third SA analyte level, Cis a constant, CT is the tendency value, Cis a constant determining how quickly the first, second, and third weights change depending on a difference between an SA analyte level and the tendency value, and S is the distribution value.

Aspects of this disclosure provide a method and a system for determining the overall analyte level based on weighted averaging of the analyte values determined for different SAs according to the divergences of the analyte values, thereby improving the accuracy of the overall analyte level.

1 FIG. 1 FIG. 1 FIG. 100 100 102 104 106 106 106 106 106 100 102 104 106 100 102 104 104 106 shows a simplified view of an exemplary analyte monitoring system(e.g., a glucose monitoring system) according to some aspects. In some aspects, as shown in, the analyte monitoring systemmay include an analyte sensor, a transceiver, and/or a user device(e.g., a smartphone). In some aspects, the user devicemay be any electronic device that is capable of conveying information to a user. In some aspects, the user devicemay convey information to a user by displaying the information on a display of the user deviceand/or by generating audio indicating the information using speakers of the user device. Although the analyte monitoring systemis illustrated inas including one analyte sensor, one transceiver, and one user device, this is not required, and, in some alternative aspects, the analyte monitoring systemmay include more than one analyte sensor, more than one transceiver(or no transceiver), and/or more than one user device.

102 102 102 In some aspects, the analyte sensormay be a fully or partially implantable (e.g., subcutaneously implantable) analyte sensor. In some alternative aspects, the analyte sensormay be a fully external analyte sensor. In some aspects, the analyte sensormay be configured to generate measurements indicative of the existence, amount, and/or concentration of an analyte (e.g., glucose) in a medium (e.g., interstitial fluid) of a living animal (e.g., a living human). In some aspects, the measurements may include, for example and without limitation, light measurements, current measurements, and/or temperature measurements.

100 102 102 102 104 103 106 107 102 102 104 103 106 107 103 107 In some aspects, the analyte monitoring systemmay generate analyte values indicating analyte levels for multiple sensing areas (SAs) of the analyte sensorusing measurements generated by the multiple SAs of the analyte sensor. In some aspects, the analyte sensormay generate the analyte values using the measurements and convey the analyte values to the transceivervia a communication channeland/or to the user deviceusing a communication channel. In some aspects in which the analyte sensorgenerates the analyte values, the analyte sensormay additionally convey the measurements to the transceivervia the communication channeland/or to the user devicevia the communication channel. Examples of the communication channelsandinclude but are not limited to near field communication (NFC), Bluetooth, Wi-Fi, a wired connection, infrared light (IR) based communication, etc.

102 104 106 102 102 102 104 106 However, it is not required that the analyte sensorgenerates the analyte values, and, in some alternative aspects, the transceiverand/or the user devicemay generate the analyte values using the measurements generated by the analyte sensor. In some aspects in which the analyte sensordoes not generate the analyte values, the analyte sensormay convey only the measurements to the transceiverand/or the user device.

104 104 102 102 103 In some aspects, the transceivermay be an externally worn transceiver (e.g., attached via an armband, wristband, waistband, or adhesive patch). In some aspects, the transceivermay be configured to remotely power and/or communicate with the analyte sensorto receive the measurements and/or analytic values from the analyte sensorvia the communication channel.

104 102 102 104 104 106 105 104 106 106 104 102 106 106 105 In some aspects, the transceivermay be configured to receive the measurements and/or analyte values from the analyte sensor. In some aspects in which the analyte sensoror transceivergenerates the analyte values, the transceivermay convey the analytic values to the user devicevia a communication channel, and the transceivermay also convey the measurements to the user device. In some aspects in which the user devicegenerates the analyte values, the transceivermay be configured to forward the measurements generated by and received from the analyte sensorto the user device, and the user devicegenerates the analyte values based on the received measurements. Examples of the communication channelmay include but are not limited to NFC, Bluetooth, Wi-Fi, wired connection, infrared light (IR) based communication, etc.

102 104 102 106 102 104 105 107 106 102 106 106 102 102 107 103 105 106 In some aspects in which the analyte sensoror the transceivergenerates the analyte values based on the measurements generated by the analyte sensor, the user devicemay be configured to receive the analyte values from the analyte sensorand/or transceivervia the communications channeland/or, and the user devicemay also receive the measurements generated by the analyte sensor. In some aspects in which the user devicegenerates the analyte values, the user devicemay be configured to receive the measurements generated by the analyte sensordirectly from the analyte sensorvia the communications channeland/or indirectly via the communications channelsand. In some aspects, the user devicemay display analyte values on a screen and/or generate audio indicating analyte values using a speaker.

1 FIG. 102 104 106 102 104 106 104 102 104 106 106 102 Althoughshows the analyte sensor, the transceiver, and the user deviceas three separate physical devices, in some aspects, two or all of the analyte sensor, the transceiver, and the user devicecan be integrated into one device. For example, the transceivermay be integrated into the analyte sensor. In another example, the transceivermay be integrated into the user device. In such example, the user devicemay be capable of communicating directly with the analyte sensor.

104 106 102 102 102 106 106 In some alternative aspects, one or more of the functions of the transceiverand the user devicemay be provided by the analyte sensor. For example, the analyte sensormay be capable of performing measurements, processing the measurements, thereby generating the analyte values, and combining the analytic values to generate an overall analytic level. After generating the overall analytic level, the analyte sensormay transmit the overall analytic level to the user devicesuch that the user devicecan output the overall analytic level.

2 FIG. 2 FIG. 102 100 102 102 250 illustrates an exemplary aspect in which the analyte sensorof the systemis a fully implantable electro-optical sensor. However, this is not required, and, in some alternative aspects, the analyte sensormay be a different type of analyte sensor (e.g., a transcutaneous electrochemical sensor) or a different type of apparatus (e.g., an insulin pump, a pacemaker, or electrical/heat therapy device). In some aspects, as shown in, the analyte sensormay include a housing(i.e., body, shell, capsule, or encasement), which may be rigid and biocompatible.

250 250 102 250 In some aspects, the housingmay be a silicon tube. However, this is not required, and, in other aspects, different materials and/or shapes may be used for the housing. In some aspects, the analyte sensormay include a transmissive optical cavity (e.g., within the housing). In some aspects, the transmissive optical cavity may be formed from a suitable, optically transmissive polymer material, such as, for example, acrylic polymers (e.g., polymethylmethacrylate (PMMA)). However, this is not required, and, in other aspects, different materials may be used for the transmissive optical cavity.

102 204 250 204 204 In some aspects, the analyte sensormay include analyte and/or interferent indicator material, which may be, for example, polymer grafts or hydrogels coated, diffused, adhered, embedded, or grown on or in one or more portions of the exterior surface of the housing. In some aspects, the analyte and/or interferent indicator materialmay be porous and may allow the analyte (e.g., glucose) in a medium (e.g., interstitial fluid) to diffuse into the analyte and/or interferent indicator material.

2 FIG. 204 1306 1308 102 1306 In some aspects, as shown in, the analyte and/or interferent indicator materialmay include analyte indicator moleculesand/or interferent indicator molecules(e.g., degradation indicator molecules). In some aspects, the analyte sensormay use the analyte indicator moleculesto measure the presence, amount, and/or concentration of an analyte (e.g., glucose, oxygen, cardiac markers, low-density lipoprotein (LDL), high-density lipoprotein (HDL), or triglycerides).

102 1308 204 1306 1308 1306 1308 In some aspects, the analyte sensormay use the interferent indicator moleculesto measure in vivo (e.g., ROS induced) signal degradation. In some aspects, in the analyte and/or interferent indicator material, the analyte indicator moleculesand/or the interferent indicator moleculesmay be copolymerized into a single biocompatible hydrogel. In some aspects, the analyte indicator moleculesand/or the interferent indicator moleculesmay have negligible spectral overlap and undergo similar degradation (e.g., similar degradation of boronic acids) in vivo.

1306 204 1306 1306 1306 1306 1306 1306 204 1306 102 In some aspects, the analyte indicator moleculesmay have one or more detectable properties (e.g., optical properties) that vary in accordance with (i) the amount or concentration of the analyte in proximity to the analyte and/or interferent indicator materialand (ii) an effect on the analyte indicator molecules(e.g., changes to the analyte indicator molecules). In some aspects, the changes to the analyte indicator moleculesmay comprise the extent to which the analyte indicator moleculeshave degraded. In some aspects, the degradation may be (at least in part) ROS-induced oxidation. In some aspects, the analyte indicator moleculesmay be fluorescent analyte indicator molecules. In some aspects, the analyte indicator moleculesmay be distributed throughout the analyte and/or interferent indicator material. In some aspects, the analyte indicator moleculesmay be phenylboronic-based analyte indicator molecules. However, a phenylboronic-based analyte indicator is not required, and, in some alternative aspects, the analyte sensormay include different analyte indicator molecules, such as, for example and without limitation, glucose oxidase-based indicators, glucose dehydrogenase-based indicators, and glucose binding protein-based indicators.

1308 1308 1308 204 1308 204 1308 204 In some aspects, the interferent indicator moleculesmay have one or more detectable properties (e.g., optical properties) that vary in accordance with changes to the interferent indicator molecules. In some aspects, the interferent indicator moleculesare not sensitive to the amount of concentration of the analyte in proximity to the analyte and/or interferent indicator material. That is, in some aspects, the one or more detectable properties of the interferent indicator moleculesdo not vary in accordance with the amount or concentration of the analyte in proximity to the analyte and/or interferent indicator material. However, this is not required, and, in some alternative aspects, the one or more detectable properties of interferent indicator moleculesmay vary in accordance with the amount or concentration of the analyte in proximity to the analyte and/or interferent indicator material.

1308 1308 1308 1308 204 1308 102 1308 In some aspects, the changes to the interferent indicator moleculesmay comprise the extent to which the interferent indicator moleculeshave degraded. In some aspects, the degradation may be (at least in part) ROS-induced oxidation. In some aspects, the interferent indicator moleculesmay be fluorescent interferent indicator molecules. In some aspects, the interferent indicator moleculesmay be distributed throughout the analyte and/or interferent indicator material. In some aspects, the interferent indicator moleculesmay be phenylboronic-based interferent indicator molecules. However, phenylboronic-based interferent indicator molecules are not required, and, in some alternative aspects, the analyte sensormay include different interferent indicator molecules, such as, for example and without limitation, amplex red-based interferent indicator molecules, dichlorodihydrofluorescein-based interferent indicator molecules, dihydrorhodamine-based interferent indicator molecules, and scopoletin-based interferent indicator molecules.

100 1308 204 1306 204 1308 1306 1308 1306 1308 1306 1306 1308 50 1306 In some aspects, the systemmay use the interferent indicator moleculesof the analyte and/or interferent indicator material, which may by sensitive to degradation by reactive oxygen species (ROS) but not sensitive to the analyte, to measure indirectly changes to the analyte indicator moleculesof an analyte and/or interferent indicator material. In some aspects, the interferent indicator moleculesmay have one or more optical properties that change with extent of oxidation and may be used as a reference for measuring and correcting for extent of oxidation of the analyte indicator molecules. In some aspects, the extent to which the interferent indicator moleculeshave degraded may correspond to the extent to which the analyte indicator moleculeshave degraded. For example, in aspects, the extent to which the interferent indicator moleculeshave degraded may be proportional to the extent to which the analyte indicator moleculeshave degraded. In some aspects, the extent to which the analyte indicator moleculeshave degraded may be calculated based on the extent to which the interferent indicator moleculeshave degraded. In some aspects, the systemmay correct for changes in the analyte indicator moleculesusing an empiric correlation established through laboratory testing.

102 318 318 318 108 1306 204 102 227 1308 204 2 FIG. In some aspects, the analyte sensormay include measurement electronics(e.g., optical measurement electronics). In some aspects, the measurement electronicsmay include one or more light sources and/or one or more photodetectors. For example, in some aspects, as shown in, the measurement electronicsmay include one or more first light sourcesthat emit first excitation light over a wavelength range that interacts with the analyte indicator moleculesin the analyte and/or interferent indicator material. In some aspects, the first excitation light may be ultraviolet (UV) light. In some aspects, the analyte sensormay include one or more second light sourcesthat emit second excitation light over a wavelength range that interacts with the interferent indicator moleculesin the analyte and/or interferent indicator material. In some aspects, the second excitation light may be, for example and without limitation, blue light.

1306 1306 1306 1306 1306 1306 331 331 1306 1306 204 1306 1306 In some aspects, the analyte indicator moleculesmay emit first emission light (e.g., fluorescent light) when irradiated by the first excitation light. In some aspects, an analyte (e.g., glucose) may bind reversibly to some of the analyte indicator molecules, and the amount of first emission light emitted by an analyte indicator moleculemay vary based on whether the analyte is bound to the analyte indicator molecule. For example, when irradiated by the first excitation light, an analyte indicator moleculemay emit a relatively large amount of first emission light if the analyte is bound to analyte indicator moleculeand may emit a relatively small amount of first emission light(or no first emission light) if analyte is not bound to the analyte indicator molecule. Therefore, the amount of first emission light emitted by the analyte indicator moleculesmay vary based on the concentration of the analyte in proximity to the analyte and/or interferent indicator material. In some aspects, the amount of first emission light emitted by the analyte indicator moleculemay also vary based on an amount of interference (e.g., the extent to which the analyte indicator moleculeshave degraded).

1308 1308 1308 1308 204 1308 1308 1308 In some aspects, the interferent indicator moleculesmay emit second emission light (e.g., fluorescent light) when irradiated by the second excitation light. In some aspects, the amount of second emission light emitted by the interferent indicator moleculesmay vary based on an amount of interference (e.g., the extent to which the interferent indicator moleculeshave degraded). In some aspects, the amount of second emission light emitted by the interferent indicator moleculesdoes not vary based on the concentration of the analyte in proximity to the analyte and/or interferent indicator material. In some aspects, degradation (e.g., oxidation) of the interferent indicator moleculesmay additionally or alternatively cause the absorption of the interferent indicator molecules(e.g., absorption of the second excitation light by the interferent indicator molecules) to change.

2 FIG. 318 102 224 226 228 318 102 224 1306 224 1306 318 226 204 226 102 228 1308 228 1308 224 204 224 227 In some aspects, as shown in, the measurement electronicsof the analyte sensormay also include one or more photodetectors,,(e.g., photodiodes, phototransistors, photoresistors, or other photosensitive elements). In some aspects, the measurement electronicsof the analyte sensormay include one or more signal photodetectorssensitive to first emission light (e.g., fluorescent light) emitted by the analyte indicator moleculessuch that a signal generated by a signal photodetectoris indicative of the level of first emission light of the analyte indicator moleculesand, thus, the amount of analyte of interest (e.g., glucose). In some aspects, the measurement electronicsmay include one or more reference photodetectorssensitive to first excitation light that may be reflected from the analyte and/or interferent indicator materialsuch that a signal generated by a photodetectorin response thereto is indicative of the level of reflected first excitation light. In some aspects, the analyte sensormay include one or more interferent photodetectorssensitive to second emission light (e.g., fluorescent light) emitted by the interferent indicator moleculessuch that a signal generated by an interferent photodetectorin response thereto that is indicative of the level of second emission light of the interferent indicator moleculesand, thus, the amount of degradation (e.g., oxidation). In some aspects, the one or more signal photodetectorsmay be sensitive to second excitation light that may be reflected from the analyte and/or interferent indicator material. In this way, the one or more signal photodetectorsmay act as reference photodetectors when the one or more second light sourcesare emitting second excitation light.

224 227 318 102 230 227 230 204 230 2 FIG. However, it is not required that the one or more signal photodetectorsact as reference photodetectors when the one or more second light sourcesare emitting second excitation light. In some alternative aspects, as shown in, the measurement electronicsof the analyte sensormay include one or more second reference photodetectorsthat act as reference photodetectors when the one or more second light sourcesare emitting second excitation light. In some aspects, the one or more second reference photodetectorsmay be sensitive to second excitation light that may be reflected from the analyte and/or interferent indicator materialsuch that a signal generated by a photodetectorin response thereto is indicative of the level of reflected second excitation light.

224 226 228 230 224 226 228 102 230 230 In some aspects, one or more of the photodetectors,,,may be covered by one or more filters that allow only a certain subset of wavelengths of light to pass through and reflect (or absorb) the remaining wavelengths. In some aspects, one or more filters on the one or more signal photodetectorsmay allow only a subset of wavelengths corresponding to first emission light and/or the reflected second excitation light. In some aspects, one or more filters on the one or more reference photodetectorsmay allow only a subset of wavelengths corresponding to the reflected first excitation light. In some aspects, one or more filters on the one or more interferent photodetectorsmay allow only a subset of wavelengths corresponding to second emission light. In some aspects in which the analyte sensorincludes one or more second reference photodetectors, one or more filters on the one or more second reference photodetectorsmay allow only a subset of wavelengths corresponding to the reflected second excitation light.

2 FIG. 318 102 232 318 482 482 224 226 228 230 232 In some aspects, as shown in, the measurement electronicsof the analyte sensormay include one or more temperature transducers. In some aspects, the measurement electronicsmay include one or more light source drivers, one or more amplifiers, one or more analog-to-digital convertors (ADCs), one or more comparators, and/or one or more multiplexors. In some aspects, the one or more ADCsmay convert analog signals output by the photodetectors,,,and/or one or more temperature transducersto digital signals.

2 FIG. 2 FIG.E 102 202 320 824 830 326 214 326 334 214 326 214 102 326 101 105 214 326 202 In some aspects, as shown in, the analyte sensormay include a charge storage device, a measurement controller, a memory, a clock, input/output (I/O) circuitry, and/or an antenna. In some aspects, the I/O circuitrymay include I/O digital circuitryand/or I/O analog circuitry (see). In some aspects, the antennamay be electrically connected to the I/O circuitry, which may use current flowing through the antennato generate power for the analyte sensorand/or to extract data from the current. In some aspects, the I/O circuitrymay also convey data (e.g., to the transceiverand/or display device) by modulating the current flowing through the antenna. In some aspects, the I/O circuitrymay (at least at times) be electrically connected to and powered by the charge storage device.

202 830 102 102 101 105 320 102 830 320 318 824 824 326 101 105 326 102 101 105 326 101 105 101 105 214 102 In some aspects, when electrically connected to and powered by the charge storage device, the clockmay provide a continuous clock for driving circuitry of the analyte sensor(e.g., even when the analyte sensoris not receiving power from an external device such as the transceiverand/or the display device). In some aspects, the measurement controllermay be a computer. In some aspects, the analyte sensormay use the continuous clock output of the clockto keep track of time and initiate autonomous, self-powered analyte measurements when appropriate (e.g., at periodic intervals, such as, for example, every minute, every two minutes, every 5 minutes, every 10 minutes, every 15 minutes, every half-hour, every hour, every two hours, every six hours, every twelve hours, or every day). In some aspects, the measurement controllermay control the measurement electronicsto perform an autonomous analyte measurement sequence, and the results of the autonomous analyte measurement may be stored in the memory. The autonomous analyte measurements may be stored in the memory. In some aspects, the I/O circuitrymay convey one or more of the stored measurements to the external device (e.g., the transceiverand/or the display device) at a later time. For example, in some request aspects, the I/O circuitrymay convey one or more of the stored measurements in response to the analyte sensorreceiving and decoding a measurement data request from the transceiverand/or the display device. In some alternative aspects, the I/O circuitrymay convey one or more of the stored measurements in response to detecting that the transceiverand/or display deviceis present (e.g., when an electrodynamic field generated by the transceiverand/or display deviceinduces a current in the antennaof the analyte sensor).

824 824 824 824 102 202 824 102 In some aspects, the memorymay be a nonvolatile storage medium. In some aspects, the memorymay be an electrically erasable programmable read only memory (EEPROM). However, in some alternative aspects, other types of nonvolatile storage media, such as flash memory, may be used. In some aspects, the memorymay include an address decoder. In some aspects, the memorymay store measurement information autonomously generated while the analyte sensoris powered from the charge storage device. In some aspects, the memorymay additionally or alternatively store one or more time-stamps identifying when the measurement data was generated, sensor calibration data, a unique sensor identification, setup information, and/or integrated circuit calibration data. In some aspects, the unique identification information may, for example, enable full traceability of the analyte sensorthrough its production and subsequent use.

2 FIG. 2 FIG. 102 318 204 318 204 102 318 102 102 In some aspects, as shown in, the analyte sensormay include one sensing device, which may include the group of measurement electronicsthat interact with (e.g., emits excitation light to and detects light reflected and/or emitted by) the analyte and/or interferent indicator material. In some aspects, the measurement electronicsthat interact with the analyte and/or interferent indicator materialmay be disposed in a particular area of the analyte sensor. In this disclosure, the area where the measurement electronicsof the analyte sensoris disposed is referred to as a sensing area (SA). Even thoughshows only one sensing device and only one SA, in some alternative aspects, the analyte sensormay include more than one sensing SA (e.g., two, three, four, five, or ten SAs), which may be part of one or more sensing devices (e.g., two, three, four, five, or ten sensing devices).

3 FIG.A 102 352 354 352 354 102 102 102 102 For example, as shown in, the analyte sensormay include first and second sensing devicesand, and each of the first and second sensing devicesandmay include two SAs for a total of four SAs for the analyte sensor. However, the number of sensing devices included in the analyte sensoris not limited to two, and the analyte sensormay include any number of sensing devices that is greater than or equal to one, such as, for example, one, three, four, five, or ten sensing devices. Similarly, the number of SAs in a sensing device is not limited to two, and a sensing device of the analyte sensormay include any number of SAs that is greater than or equal to one, such as, for example, one, three, four, five, or ten SAs.

3 FIG.A 2 FIG. 352 354 318 204 250 352 354 202 214 102 214 352 354 202 In some aspects, as shown in, the sensing devicesandmay each include one or more groups of measurement electronics (“MEs”) (e.g.,shown in) that interacts with analyte and/or interferent indicator materialon a portion of the exterior surface of the housing. In some aspects, the sensing devicesandmay share a charge storage deviceand/or an antenna. That is, in some aspects in which the analyte sensorincludes multiple sensing devices, the antennamay be electrically connected to the circuitry of the multiple sensing devices (e.g., sensing devicesand), and the charge storage devicemay be connected to the circuitry of the multiple sensing devices.

3 FIG.A 3 FIG.A 3 FIG.A 352 354 352 302 304 354 306 308 102 302 308 In some aspects, as further shown in, in some aspects, each of the sensing devicesandmay include more than one group of MEs. For example, as shown in, the sensing devicemay include a first ME groupin a sensing area (SA) #1 and a second ME groupin SA #2. Similarly, the sensing devicemay include a third ME groupin SA #3 and a fourth ME groupin SA #4. The SAs #1-4 are four different areas of the analyte sensorwhere the ME groups-are disposed. As noted above, even thoughshows that the number of SAs (i.e., the number of ME groups) included in each sensing device is two, in some alternative aspects, the number of SAs in each sensing device may be a different number.

302 308 108 224 226 227 228 230 232 482 302 308 108 224 226 227 228 230 232 482 302 308 108 224 226 227 228 230 232 482 302 108 224 226 227 228 230 232 482 304 108 224 226 227 228 230 302 304 482 232 2 FIG. In some aspects, each of the ME groups-may include one or more of the elements,,,,,,, and/orshown in. In some aspects, each of the ME groups-may include the elements,,,,,,, and/or. In some alternative aspects, the ME groups-may share some of the elements,,,,,,, and/or. More specifically, in one example, the first ME groupmay include the elements,,,,,,, and, but the second ME groupmay only include the elements,,,,, and. In this example, the ME groupsandmay share the use of the ADCand the temperature transducer.

3 FIG.A 3 FIG.A 102 352 302 304 306 308 In some aspects, as shown in, in some aspects, the analyte sensormay include more than one ME groups for generating measurements that may be used for determining analyte values. For example, as shown in, the sensing devicemay include the four ME groups,,, andfor generating measurements for the four SAs #1-#4, respectively.

102 102 104 104 106 106 In some aspects, each ME group may be configured to generate a set of measurements for an SA, and the measurements generated from the ME groups may be used to generate analyte values for the SAs. In some aspects, the generated analyte values for the SAs may be combined to calculate an overall analyte level. More specifically, in one example, each ME group included in the analyte sensormay generate measurements, and the analyte sensormay send the measurements to the transceiver. Based on the received measurements, the transceivermay calculate analyte values for the SAs, combine the calculated analyte values for the SAs to calculate an overall analyte level, and send the calculated overall analyte value to the user device. The user devicemay output (e.g., display or generate a sound) the received overall analyte level.

3 3 FIGS.B-E 3 FIG.B 3 FIG.C 3 FIG.D 3 FIG.E 3 3 FIGS.B-E 322 302 324 304 326 306 328 308 1 2 3 However, as illustrated in, there may be a scenario where the set of measurements generated from one of the ME groups is diverged from the remaining sets of measurements generated from other ME groups.shows a setof analyte values generated based on measurements generated by the first ME groupin the SA #1.shows a setof analyte values generated based on measurements generated by the second ME groupin the SA #2.shows a setof analyte values generated based on measurements generated by the third ME groupin the SA #3.shows a setof analyte values generated based on measurements generated by the fourth ME groupin the SA #4. The analyte values included in each set are generated at different timings. For example, the first analyte value in each set is generated at t, the second analyte value in each set is generated at t, and the third analyte value in each set is generated at t. In other words, each set of analyte values is generated during a time window of N (here N=3). Here, the time window of N means a time interval comprising N number of sub-intervals having the same time length. Even thoughshow that N is equal to three, N can be any number that is greater than 0. In other words, the number of analyte values included in each set may be any number that is greater than 0 (e.g., N may be equal to one, two, four, five, eight, ten, fifteen, or twenty analyte values).

3 3 FIGS.B-E 326 306 322 324 328 326 As shown in, the third setof analyte values generated based on measurements generated by the third ME groupin the SA #3 is diverged from the remaining sets,, andof analyte values generated based on measurements generated by other ME groups. In this scenario, it may be desirable to exclude or give less weight to the third setof analyte values in calculating the combined analyte level. Thus, according to some aspects, the contribution of a set of analyte values to the combined analyte level may be adjusted based on the divergence of the set of analyte values with respect to other sets of analyte values.

4 FIG. 400 100 102 104 106 100 400 104 400 102 106 400 400 302 308 shows one exemplary processfor determining whether a set of analyte values generated based on measurements by an ME group associated with an SA (i.e., a set of analyte values generated for an SA) is diverged from other sets of analyte values generated for other SAs, according to some aspects. In some aspects, the analyte monitoring system(e.g., the analyte sensor, transceiver, and/or user deviceof the analyte monitoring system) may perform one or more steps of the process. In some aspects, the transceivermay perform one or more steps of the process, and, in some alternative aspects, the analyte sensoror the user devicemay performed one or more steps of the process. In some aspects, the processmay be performed for each of the ME group-.

4 FIG. 400 402 402 402 326 306 a In some aspects, as shown in, the processmay include a step. The stepmay include calculating the mean value (mean) of N most recent samples (a.k.a., “analyte values”) generated by a certain ME group. For example, the stepmay include calculating the mean value of three samples (i.e., N=3) from the setof analyte values generated based on measurements by the third ME groupin the SA #3.

4 FIG. 4 FIG. 400 404 404 404 322 324 328 302 304 308 404 402 402 404 b b In some aspects, as shown in, the processmay include a step. The stepmay include calculating the mean value (mean) and the standard deviation (std) of N samples generated based on measurements by the remaining ME groups. For example, the stepmay include calculating the mean value and the standard deviation of nine samples from the sets,, andof analyte values generated based on measurements by the ME groups,, and. Althoughshows that the stepis performed after the step, in some alternative aspects, the stepmay be performed after or simultaneously with the step.

4 FIG. 400 406 406 306 a In some aspects, as shown in, the processmay include a step. The stepmay include computing the Mahalanobis distance metric of the certain ME group (e.g., the third ME groupin the SA #3) from the remaining ME groups. In some aspects, the Mahalanobis distance metric (d) may be calculated as follows:

1 2 3 where each of C, C, and Cis a constant.

b b 102 In some aspects, meanand stdmay be calculated based not only on the samples from the ME groups included in an analyte sensing device but also on the samples from the ME groups included in two or more analyte sensing devices included in the device.

4 FIG. 400 408 408 In some aspects, as shown in, the processmay include a step. The stepmay include comparing the Mahalanobis distance metric to a threshold value. If the Mahalanobis distance metric is greater than or equal to the threshold value, the certain ME group may be determined to be diverged from other ME groups. In contrast, if the Mahalanobis distance metric is less than the threshold value, the certain ME group may be determined to be not diverged from other ME groups.

In some alternative aspects, instead of the standard deviation (SD), another distribution parameter may be used. For example, in some alternative aspects, either an interquartile range (IQR) or an interdecile range (IDR) may be used instead.

306 302 In some aspects, after determining that a certain ME group is diverged from other ME groups, the Mahalanobis distance metric of the other ME groups may be calculated or recalculated by excluding the samples generated by the diverged ME group (i.e., outlier). For example, if the third ME groupis determined to be diverged, the Mahalanobis distance metric of the first ME groupmay be calculated as follows:

302 304,308 304,308 322 302 324 328 304 308 324 328 304 308 306 where meanis the mean value of the three samples from the setof analyte values generated based on measurements by the first ME group, meanis the mean value of the six samples from the setsandof the second and fourth ME groupsand, and stdis the standard deviation of the six samples from the setsandof the second and fourth ME groupsand. Here, the samples of the diverged ME group (i.e., the third ME group) may be excluded from calculating the mean value and the standard deviation.

400 An example of the computer code implementing the steps of the processis shown below.

class Distances(BaseFeature):  “‘   Mahalanobis Distance of last window value to others   Cross channel divergence metric  ”’ —— ——  definit(self, columns=‘all’, window_sizes=[10]):   “‘   Args:    columns (str or list, optional): If string, should be ‘all’. If list, then      is a list of columns names to which the feature functionality should be applied.      Some features use specific columns and ignore this. Defaults to ‘all’.    window_size (list, int or None, optional): If None, expect feature to       not use a sliding window in its processing. If an int or list of int,       feature can apply its methods to sliding windows of those sizes. Defaults to       None.   Argument info available to all features; whether/how they use the info or not is their choice.   ”’ —— ——   super( ).init(columns, window_sizes) #**************************************************************************  def generate(self, am):   “‘   Args:    am (DataFrame): Analysis matrix.   Returns:    DataFrame: New feature data.   ”’   # Set up groups of columns across which to compute divergence   matrix = am if self.columns == ‘all’ else am[self.columns]   cols = du.group_columns(matrix.columns)   col_groups = [d for c in cols.values( ) if isinstance(c, dict) for d in c.values( )]   col_flat = [j for i in col_groups for j in i]   output_names = [(self.get_class( ) + ‘:zScore(‘ + i + ’,’, self.get_class( ) + ‘:zScoreInstant(‘ + i + ’,’) for i in col_flat]   output_flat = [j for i in output_names for j in i]   # Compute the divergence of each channel within each group   div_fnc = partial(self._divergence, column_groups=col_groups)   div_data = _slide_window(matrix, self.window_sizes, ‘extend’, div_fnc, output_flat)   return div_data #**************************************************************************  def _divergence(self, am, column_groups):   “‘   Args:    am (DataFrame): Analysis matrix.   Returns:    list: New row of feature data.   ”’   results = [ ]   for col_group in column_groups:    if len(col_group) > 1:     for c in col_group:      # Compute Mahalanobis distance from test channel to other channels in group      background_columns = [i for i in col_group if i != c]      background_data = am[background_columns].to_numpy( )      background_mean = np.mean(background_data, axis=1) if len(background_data) > 0 else 1      foreground_data = am[c].to_numpy( )      mean_delta = np.mean(np.abs(foreground_data − background_mean))      std_background = np.std(background_data.flatten( ))      if std_background > 0:       results.append(mean_delta / std_background) # z_score      else:       results.append(0.0)    else:     results.append(0.0)   return results

306 overall After identifying a diverged ME group (e.g., the third ME group), an overall analyte level may be determined based on a weighted combination of the analyte values generated by the ME groups. For example, the overall analyte level (AL) may be calculated as follows:

overall a a where ALis the overall analyte level, M is the number of ME groups/SAs, wis a weight value assigned to a certain ME group, and AVis an analyte value generated by a certain ME group.

a M a M In some aspects, wof a certain ME group may be a function of the Mahalanobis distance metric (d) of the certain ME group—i.e., w=f(d). In one example,

4 M where Cis a constant and dis the Mahalanobis distance metric. In these aspects, the more a certain ME group is diverged from the rest of the ME groups, less weight is given to the diverged ME group, and thus less contribution is made by the samples of the diverged ME group to the overall analyte level.

In some aspects, once a certain ME group is determined to be diverged from other ME groups, the samples generated by the diverged ME group may be excluded from being used in calculating the overall analyte level.

a 306 302 304 308 302 304 306 308 Alternatively, in some aspects, wof a certain ME group (e.g., the third ME group) may set to be a function of 1) a difference between an analyte value generated from the certain ME group and a central tendency value (CT) (e.g., mean, median, bi-mean, weighted mean) of the analyte values generated from the remaining ME groups (e.g., the ME groups,, and) or all ME groups (e.g., the ME groups,,, and) and 2) a measure of spread (S) (e.g., SD, IQR, IDR) of the analyte values generated from the remaining ME groups or all ME groups. For example,

5 6 7 where each of C, C, and Cis a constant.

The following paragraphs describe detailed exemplary methods of calculating the overall analyte level according to some aspects. In the paragraphs below, glucose is used as an example of the analyte.

n a n In some aspects, the final glucose level (i.e., the overall analyte level) may be calculated as a weighted average of glucose values generated for all SAs using normalized weights w, where the sum of the normalized weights wis 1. For example, the final glucose level (GLU) may be calculated as follows:

a where GLUis a glucose value generated by a certain ME group in a certain SA and N is the number of ME groups or the number of SAs.

n n a The uniformity of the weighting may be controlled through the normalization process by the exponent k. For example, when k=0, the weighting is uniform (ω=1/N). As k increases, weighting becomes 0 for all areas but the one with the highest unnormalized weight. In one example, the weight wcan be calculated as follows:

un a corresponds to an unnormalized weight wmodified by the exponent k.

un a Q a G a un a In some aspects, the unnormalized weight wmay be composed of a weighting coming from an independent quality assessment of the data, ω, and a weighting that comes from the distribution of the glucose values across the different areas, ω. For example, the unnormalized weight wmay be calculated as follows:

In some aspects, MSP is a metric for real time assessment of sensor performance (MSP), which is explained in U.S. Pat. No. 10,869,624, which is hereby incorporated by reference in its entirety. In some aspects, MEP is a metric for electronic performance (MEP), which is explained in U.S. Pat. No. 11,701,038, which is hereby incorporated by reference in its entirety.

Q a In one example, the weighting ωcoming from the independent quality assessment of the data may be calculated as follows:

Q a In another example, the weighting ωcoming from the independent quality assessment of the data may be calculated as follows:

G a In one example, the weighting ωthat comes from the distribution of the glucose values across the different area may be calculated as follows:

Here, CT is a central tendency such as mean, median, bi-mean or weighted mean, S is a measure of spread such SD, IQR, or IDR, c is a parameter that controls how quickly the weights roll off. According to the above formula, when an SA's glucose value differs from the central tendency by more than cS, its weight will go to 0 (considered a complete outlier). In some aspects, 1<c<2. Note that the weighted mean can be used by assuming uniform weighting for CT and then iteratively calculating new weights using the weights from the last iteration for CT.

G a In another example, the weighting ωthat comes from the distribution of the glucose values across the different areas may be calculated as follows:

Here, CT is a central tendency such as mean, median, bi-mean or weighted mean, S is a measure of spread such SD, IQR, or IDR, c is a parameter that controls how quickly the weights roll off. According to the above formula, when an SA's glucose value differs from the central tendency by more than cS, its weight will go to 0 (considered a complete outlier). In some aspects, 1<c<2. Note that the weighted mean can be used by assuming uniform weighting for CT and then iteratively calculating new weights using the weights from the last iteration for CT.

As explained above, in some aspects, the divergence of the analyte values generated for a certain SA with respect to the analyte values generated for other SAs is calculated based on the Mahalanobis distance metric. However, in other aspects, the divergence of analyte values can be calculated as follows:

Area n n a a n Dev(t) is a value indicating the divergence of analyte values generated for a certain SA at time=t, Nis the number of different SAs, GLU(t) is a Glucose level measured by a ME group in a certain SA, and CT is a central tendency of analyte values generated for all SAs (or all SAs excluding the certain SA). In some aspects,

In some aspects, the divergence of analyte values may be calculated not only per SA but also per time. In such aspects, the divergence of analyte values can be calculated as follows:

Area,Time m m a a n Dev(t) is a value indicating the divergence of analyte values generated for a certain SA at time=t, Nis the number of different SAs, GLU(t) is a Glucose level measured by a ME group in a certain SA, CT is a central tendency of analyte values generated for all SAs (or all SAs excluding the certain SA), and 1-L is the number of time intervals for measuring the analyte values.

102 352 As explained above, in case the analyte sensor(or the analyte sensing device) includes more than one ME groups in a certain SA of the device, multiple sets of analyte values are generated. However, there may be a scenario where a set of analyte values generated for a certain SA is diverged from other sets of analyte values, and thus the diverged set of analyte values constitutes an “outlier” or low quality measurements. In this scenario, in calculating the overall analyte level, it may be beneficial to “de-weight” or exclude such outlier/low quality measurements. According to some aspects of this disclosure, such outlier/low quality measurements is detected/identified using a distribution of all analyte values and the contribution of outlier/low quality measurements towards the overall analyte level is adjusted, thereby improving the accuracy of determining the overall analyte level.

5 FIG. 500 100 102 104 106 100 104 500 102 106 500 shows a processperformed by the analyte monitoring system(e.g., the analyte sensor, transceiver, and/or user deviceof the analyte monitoring system) according to some aspects. In some aspects, the transceivermay perform one or more steps of the process, and, in some alternative aspects, the analyte sensoror the user devicemay performed one or more steps of the process.

5 FIG. 500 502 502 322 302 102 502 104 302 102 102 502 106 302 102 102 502 102 In some aspects, as shown in, the processmay include a step. The stepmay include generating a first setof one or more analyte values using first measurement electronicsof a first sensing area (SA) of the analyte sensor. In some aspects, the stepmay, for example, be performed by the transceiverusing measurements generated by the measurement electronicsof the first SA of the analyte sensorand conveyed from the analyte sensor. In some alternative aspects, stepmay be performed by the user deviceusing measurements generated by the measurement electronicsof the first SA of the analyte sensorand conveyed from the analyte sensor. In some further alternative aspects, stepmay be performed by the analyte sensor.

5 FIG. 500 504 504 324 304 102 504 104 304 102 102 504 106 304 102 102 504 102 In some aspects, as shown in, the processmay include a step. The stepmay include generating a second setof one or more analyte values using second measurement electronicsof a second SA of the analyte sensor. In some aspects, stepmay, for example, be performed by the transceiverusing measurements generated by the measurement electronicsof the second SA of the analyte sensorand conveyed from the analyte sensor. In some alternative aspects, stepmay be performed by the user deviceusing measurements generated by the measurement electronicsof the second SA of the analyte sensorand conveyed from the analyte sensor. In some further alternative aspects, stepmay be performed by the analyte sensor.

5 FIG. 5 FIG. 500 506 506 326 306 102 506 104 306 102 102 506 106 306 102 102 506 102 506 504 504 502 502 504 506 In some aspects, as shown in, the processmay include a step. The stepmay include generating a third setof one or more analyte values using third measurement electronicsof a third SA of the analyte sensor. In some aspects, stepmay, for example, be performed by the transceiverusing measurements generated by the measurement electronicsof the third SA of the analyte sensorand conveyed from the analyte sensor. In some alternative aspects, stepmay be performed by the user deviceusing measurements generated by the measurement electronicsof the third SA of the analyte sensorand conveyed from the analyte sensor. In some further alternative aspects, stepmay be performed by the analyte sensor. Althoughshows that stepis performed after the stepand that stepis performed after step, in some alternative aspects, the step,, andmay be formed in a different order or simultaneously.

5 FIG. 500 328 308 102 500 102 In some aspects, although not shown in, the processmay include an optional step of generating a fourth setof one or more analyte values using fourth measurement electronicsof a fourth SA of the analyte sensor. In some aspects, the processmay include optional steps of generating additional sets of one or more analyte values using additional measurement electronics of additional SAs of the analyte sensor.

5 FIG. 5 FIG. 500 508 508 322 324 326 328 500 510 In some aspects, as shown in, the processmay include a step. The stepmay include determining a distribution value based on a plurality of sets of analyte values including the first, second, and/or third sets,, and/orof analyte values. In some aspects, the plurality of sets of analyte values may include the fourth setof analyte values. In some aspects, the distribution value may indicate a distribution of the plurality of sets of analyte values. In some aspects, as shown in, the processmay include a stepof determining a combined analyte level based at least on the plurality of sets of analyte values and the distribution value.

322 302 102 324 304 102 326 306 102 328 308 102 In some aspects, the first setof analyte values may include a plurality of analyte values generated for different instances of time using the first measurement electronicsof the first SA of the analyte sensor, the second setof analyte values includes a plurality of analyte values generated for the different instances of time using the second measurement electronicsof the second SA of the analyte sensor, and the third setof analyte values includes a plurality of analyte values generated for the different instances of time using the third measurement electronicsof the third SA of the analyte sensor. In some aspects, the fourth setof analyte values may include a plurality of analyte values generated for different instances of time using the fourth measurement electronicsof the fourth SA of the analyte sensor.

500 322 324 326 500 510 In some aspects, the processmay include determining whether the first setof analyte values satisfies a condition, determining whether the second setof analyte values satisfies the condition, and determining whether the third setof analyte values satisfies the condition. In some aspects, the processmay include, based on determining that the first and second sets of analyte values do not satisfy the condition and the third set of analyte values satisfies the condition, not selecting the first and second SAs and selecting the third SA, and the combined analyte level may be determined in stepbased on the selection of the third SA.

326 328 In some aspects, determining the distribution value may include: calculating a first tendency value representing the third setof analyte values and calculating a second tendency value representing the plurality of sets of analyte values. In some aspects, whether the third setof analyte values satisfies the condition may be determined based at least on the first tendency value, the second tendency value, and the distribution value.

326 In some aspects, the first tendency value may be one of a mean or a median of the third setof analyte values, the second tendency value may be one of a mean or a median of the plurality of sets of analyte values, and the distribution value may be one of a standard deviation, an interquartile range, or an interdecile range of the plurality of sets of analyte values.

326 326 In some aspects, determining whether the third setof analyte values satisfies the condition may include: calculating a comparative value based on the first tendency value, the second tendency value, and the distribution value; determining whether the comparative value is greater than a threshold value; and determining that the third setof analyte values satisfies the condition based on whether the comparative value is greater than the threshold value.

In some aspects, the comparative value may be calculated as follows:

1 2 3 1 2 2 where d is the comparative value, Cis a first constant, Cis a second constant, Cis a third constant, Tis the first tendency value, Tis the second tendency value, and Dis the distribution value.

326 In some aspects, if the third setof analyte values is determined to satisfy the condition, the distribution value may be determined not based on the third set of analyte values.

322 324 326 In some aspects, determining the combined analyte level may include: calculating a first SA analyte level for the first SA based on the first setof analyte values; determining a first weight for the first SA analyte level; calculating a second SA analyte level for the second SA based on the second setof analyte values; determining a second weight for the second SA analyte level; calculating a third SA analyte level for the third SA based on the third setof analyte values; and determining a third weight for the third SA analyte level. In some aspects, the combined analyte level may be determined based on the first SA analyte level, the first weight, the second SA analyte level, the second weight, the third SA analyte level, and the third weight.

In some aspects, the first weight may be determined based at least on: the first SA analyte level; a tendency value representing the plurality of sets of analyte values; and the distribution value. In some aspects, the second weight may be determined based at least on: the second SA analyte level; the tendency value; and the distribution value. In some aspects, the third weight may be determined based at least on: the third SA analyte level; the tendency value; and the distribution value.

In some aspects, the first weight may have a negative correlation with a difference between the first SA analyte level and the tendency value increases; the second weight may have a negative correlation with a difference between the second SA analyte level and the tendency value increases; and the third weight may have a negative correlation with a difference between the third SA analyte level and the tendency value increases.

In some aspects, the tendency value may be one of a mean or a median of the plurality of sets of analyte values, and the distribution value may be one of a standard deviation, an interquartile range, or an interdecile range of the plurality of sets of analyte values.

In some aspects, the first weight may equal

the second weight may equal

and the third weight may equal

1 SA1 SA2 SA3 2 3 where Cis a constant, ALis the first SA analyte level, ALis the second SA analyte level, ALis the third SA analyte level, Cis a constant, CT is the tendency value, Cis a constant determining how quickly the first, second, and third weights change depending on a difference between an SA analyte level and the tendency value, and S is the distribution value.

500 100 102 502 504 506 508 510 A1. A method () performed by an analyte monitoring system () comprising an analyte sensor (), the method comprising: generating (s) a first set of one or more analyte values using first measurement electronics of a first sensing area (SA) of the analyte sensor; generating (s) a second set of one or more analyte values using second measurement electronics of a second SA of the analyte sensor, wherein the first and second SAs are different; generating (s) a third set of one or more analyte values using third measurement electronics of a third SA of the analyte sensor, wherein the first, second, and third SAs are different; determining (s) a distribution value based on a plurality of sets of analyte values including the first, second, and/or third sets of analyte values, wherein the distribution value indicates a distribution of the plurality of sets of analyte values; and determining (s) a combined analyte level based at least on the plurality of sets of analyte values and the distribution value.

A2. The analyte monitoring system of embodiment A1, wherein: the first set of analyte values includes a plurality of analyte values generated for different instances of time using the first measurement electronics of the first SA of the analyte sensor, the second set of analyte values includes a plurality of analyte values generated for the different instances of time using the second measurement electronics of the second SA of the analyte sensor, and the third set of analyte values includes a plurality of analyte values generated for the different instances of time using the third measurement electronics of the third SA of the analyte sensor.

A3. The method of embodiment A1 or A2, comprising: determining whether the first set of analyte values satisfies a condition; determining whether the second set of analyte values satisfies the condition; determining whether the third set of analyte values satisfies the condition; and, based on determining that the first and second sets of analyte values do not satisfy the condition and the third set of analyte values satisfies the condition, not selecting the first and second SAs and selecting the third SA, wherein the combined analyte level is determined based on the selection of the third SA.

A4. The method of embodiment A3, wherein: the analyte sensor comprises a plurality of SAs including the first, second, and third SAs; the method comprises generating the plurality of set of analyte values using measurement electronics of the plurality of SAs of the analyte sensor; determining the distribution value comprises: calculating a first tendency value representing the third set of analyte values, and calculating a second tendency value representing the plurality of sets of analyte values, and whether the third set of analyte values satisfies the condition is determined based at least on the first tendency value, the second tendency value, and the distribution value.

A5. The method of embodiment A4, wherein: the first tendency value is one of a mean or a median of the third set of analyte values, the second tendency value is one of a mean or a median of the plurality of sets of analyte values, and the distribution value is one of a standard deviation, an interquartile range, or an interdecile range of the plurality of sets of analyte values.

A6. The method of embodiment A4 or A5, wherein determining whether the third set of analyte values satisfies the condition comprises: calculating a comparative value based on the first tendency value, the second tendency value, and the distribution value; determining whether the comparative value is greater than a threshold value; and determining that the third set of analyte values satisfies the condition based on whether the comparative value is greater than the threshold value.

A7. The method of embodiment A6, wherein the comparative value is calculated as follows:

1 2 3 1 2 2 where d is the comparative value, Cis a first constant, Cis a second constant, Cis a third constant, Tis the first tendency value, Tis the second tendency value, and Dis the distribution value.

A8. The method of any one of embodiments A3-A7, wherein, if the third set of analyte values is determined to satisfy the condition, the distribution value is determined not based on the third set of analyte values.

A9. The method of any one of embodiments A1-A7, wherein determining the combined analyte level comprises: calculating a first SA analyte level for the first SA based on the first set of analyte values; determining a first weight for the first SA analyte level; calculating a second SA analyte level for the second SA based on the second set of analyte values; determining a second weight for the second SA analyte level; calculating a third SA analyte level for the third SA based on the third set of analyte values; and determining a third weight for the third SA analyte level; wherein the combined analyte level is determined based on the first SA analyte level, the first weight, the second SA analyte level, the second weight, the third SA analyte level, and the third weight.

A10. The method of embodiment A9, wherein: the first weight is determined based at least on: the first SA analyte level; a tendency value representing the plurality of sets of analyte values; and the distribution value, the second weight is determined based at least on: the second SA analyte level; the tendency value; and the distribution value, and the third weight is determined based at least on: the third SA analyte level; the tendency value; and the distribution value.

A11. The method of embodiment A10, wherein: the first weight has a negative correlation with a difference between the first SA analyte level and the tendency value increases; the second weight has a negative correlation with a difference between the second SA analyte level and the tendency value increases; and the third weight has a negative correlation with a difference between the third SA analyte level and the tendency value increases.

A12. The method of embodiment A10 or A11, wherein: the tendency value is one of a mean or a median of the plurality of sets of analyte values, and the distribution value is one of a standard deviation, an interquartile range, or an interdecile range of the plurality of sets of analyte values.

A13. The method of any one of embodiments A10-A12, wherein;

1 SA1 SA2 SA3 2 3 where Cis a constant, ALis the first SA analyte level, ALis the second SA analyte level, ALis the third SA analyte level, Cis a constant, CT is the tendency value, Cis a constant determining how quickly the first, second, and third weights change depending on a difference between an SA analyte level and the tendency value, and S is the distribution value.

100 102 106 502 504 506 508 510 B1. An analyte monitoring system () comprising: an analyte sensor (); a user device (), wherein the analyte monitoring system is configured to: generate () a first set of one or more analyte values using first measurement electronics of a first sensing area (SA) of the analyte sensor; generate () a second set of one or more analyte values using second measurement electronics of a second SA of the analyte sensor, wherein the first and second SAs are different; generate () a third set of one or more analyte values using third measurement electronics of a third SA of the analyte sensor, wherein the first, second, and third SAs are different; determine () a distribution value based on a plurality of sets of analyte values including the first, second, and/or third sets of analyte values, wherein the distribution value indicates a distribution of the plurality of sets of analyte values; and determine () a combined analyte level based at least on the plurality of sets of analyte values and the distribution value.

B2. The analyte monitoring system of embodiment B1, wherein: the first set of analyte values includes a plurality of analyte values generated for different instances of time using the first measurement electronics of the first SA of the analyte sensor, the second set of analyte values includes a plurality of analyte values generated for the different instances of time using the second measurement electronics of the second SA of the analyte sensor, and the third set of analyte values includes a plurality of analyte values generated for the different instances of time using the third measurement electronics of the third SA of the analyte sensor.

B3. The analyte monitoring system of embodiment B1 or B2, wherein the analyte monitoring system is configured to: determine whether the first set of analyte values satisfies a condition; determine whether the second set of analyte values satisfies the condition; determine whether the third set of analyte values satisfies the condition; and, based on determining that the first and second sets of analyte values do not satisfy the condition and the third set of analyte values satisfies the condition, not select the first and second SAs and selecting the third SA, wherein the combined analyte level is determined based on the selection of the third SA.

B4. The analyte monitoring system of embodiment B3, wherein: the analyte sensor comprises a plurality of SAs including the first, second, and third SAs; the analyte monitoring system is configured to generate the plurality of set of analyte values using measurement electronics of the plurality of SAs of the analyte sensor; determining the distribution value comprises: calculating a first tendency value representing the third set of analyte values, and calculating a second tendency value representing the plurality of sets of analyte values; and whether the third set of analyte values satisfies the condition is determined based at least on the first tendency value, the second tendency value, and the distribution value.

B5. The analyte monitoring system of embodiment B4, wherein: the first tendency value is one of a mean or a median of the third set of analyte values, the second tendency value is one of a mean or a median of the plurality of sets of analyte values, and the distribution value is one of a standard deviation, an interquartile range, or an interdecile range of the plurality of sets of analyte values.

B6. The analyte monitoring system of embodiment B4 or B5, wherein determining whether the third set of analyte values satisfies the condition comprises: calculating a comparative value based on the first tendency value, the second tendency value, and the distribution value; determining whether the comparative value is greater than a threshold value; and determining that the third set of analyte values satisfies the condition based on whether the comparative value is greater than the threshold value.

B7. The analyte monitoring system of embodiment B6, wherein the comparative value is calculated as follows:

1 2 3 1 2 2 where d is the comparative value, Cis a first constant, Cis a second constant, Cis a third constant, Tis the first tendency value, Tis the second tendency value, and Dis the distribution value.

B8. The analyte monitoring system of any one of embodiments B3-B7, wherein, if the third set of analyte values is determined to satisfy the condition, the distribution value is determined not based on the third set of analyte values.

B9. The analyte monitoring system of any one of embodiments B1-B7, wherein determining the combined analyte level comprises: calculating a first SA analyte level for the first SA based on the first set of analyte values; determining a first weight for the first SA analyte level; calculating a second SA analyte level for the second SA based on the second set of analyte values; determining a second weight for the second SA analyte level; calculating a third SA analyte level for the third SA based on the third set of analyte values; and determining a third weight for the third SA analyte level; wherein the combined analyte level is determined based on the first SA analyte level, the first weight, the second SA analyte level, the second weight, the third SA analyte level, and the third weight.

B10. The analyte monitoring system of embodiment B9, wherein: the first weight is determined based at least on: the first SA analyte level, a tendency value representing the plurality of sets of analyte values, and the distribution value; the second weight is determined based at least on: the second SA analyte level, the tendency value, and the distribution value; and the third weight is determined based at least on: the third SA analyte level, the tendency value, and the distribution value.

B11. The analyte monitoring system of embodiment B10, wherein: the first weight has a negative correlation with a difference between the first SA analyte level and the tendency value increases; the second weight has a negative correlation with a difference between the second SA analyte level and the tendency value increases; and the third weight has a negative correlation with a difference between the third SA analyte level and the tendency value increases.

B12. The analyte monitoring system of embodiment B10 or B11, wherein: the tendency value is one of a mean or a median of the plurality of sets of analyte values, and the distribution value is one of a standard deviation, an interquartile range, or an interdecile range of the plurality of sets of analyte values.

B13. The analyte monitoring system of any one of embodiments B10-B12, wherein;

1 SA1 SA2 SA3 2 3 where Cis a constant, ALis the first SA analyte level, ALis the second SA analyte level, ALis the third SA analyte level, Cis a constant, CT is the tendency value, Cis a constant determining how quickly the first, second, and third weights change depending on a difference between an SA analyte level and the tendency value, and S is the distribution value.

While various aspects are described herein, it should be understood that they have been presented by way of example only, and not limitation. Thus, the breadth and scope of this disclosure should not be limited by any of the above-described exemplary aspects. Moreover, any combination of the above-described elements in all possible variations thereof is encompassed by the disclosure unless otherwise indicated herein or otherwise clearly contradicted by context.

As used herein transmitting a message “to” or “toward” an intended recipient encompasses transmitting the message directly to the intended recipient or transmitting the message indirectly to the intended recipient (i.e., one or more other nodes are used to relay the message from the source node to the intended recipient). Likewise, as used herein receiving a message “from” a sender encompasses receiving the message directly from the sender or indirectly from the sender (i.e., one or more nodes are used to relay the message from the sender to the receiving node). Further, as used herein “a” means “at least one” or “one or more.”

Additionally, while the processes described above and illustrated in the drawings are shown as a sequence of steps, this was done solely for the sake of illustration. Accordingly, it is contemplated that some steps may be added, some steps may be omitted, the order of the steps may be re-arranged, and some steps may be performed in parallel.